This invention relates to a signal processor of a vehicle-mounted array radar apparatus having a plurality of antenna components.
Vehicle-mounted radar apparatus are known for predicting the presence or a movement state of a preceding target, such as a preceding vehicle in order to prevent collisions and to maintain an inter-vehicle distance with respect thereto.
Some vehicle-mounted array radar apparatus may have a plurality of observation means, a plurality of means for respectively extracting distance components, a plurality of means for respectively estimating correlation matrices with exponential smoothing, and means for estimating presence and movement state of a target.
FIG. 2 is a block diagram showing a schematic structure of a conventional vehicle-mounted array radar apparatus. FIG. 3 is a view showing a structure of a FM-CW radar which is an instance of the observation means. FIG. 4 is a view showing a structure of a pulse radar which is an instance of the observation means.
A conventional vehicle-mounted array radar apparatus as shown in FIG. 2. Such a radar apparatus has observation means 1 through K denoted with reference numerals OB, means for respectively extracting distance components 1 through K denoted with reference numerals DS, means for respectively estimating correlation matrices with exponential smoothing 1 through N denoted with reference numerals RM, and means for estimating presence and movement state of target denoted with a reference numeral OM.
In operation, the observation means p (array component p=1, 2, . . . K) acquires an observation signal which includes information regarding the presence and movement state of a target obtained from a transmitted signal which is a radar wave and a received signal received by an antenna. The movement states of a target include positions (distance and azimuth), velocities, accelerations and the like. As shown in FIG. 2, the observation means p (array component p=1, 2, . . . K) outputs observation signals XTp(t1), XTp(t2), XTp(t3), . . . XTp(tM) which are sampled at times t1, t2, . . . tM. M numbers of the observation signals which are sampled at times t1, t2, . . . tM is referred to as one snapshot. The observation means 1 through K correspond to array components 1 through K. A linear array is known as a physical arrangement of the array components.
An example of a FM-CW radar will now be described. A FM-CW radar, which is the observation means OB, has an oscillator 1, a transmitting amplifier 2, a transmitting antenna 3, a receiving antenna 5, a receiving amplifier 6, a distributor 7, a mixer 9, a filter 10, and an A/D converter 11, as shown in FIG. 3. The oscillator 1 oscillates millimetric-wave signals which are modulated such that the frequency increases and decreases linearly with passage of time to form a triangular wave form, and the millimetric-wave signal is emitted as a transmitted signal S1 via the transmitting amplifier 2 and the transmitting antenna 3. At the same time, the reflected wave of the transmitted signal is received as a received signal S2 through the receiving antenna 5. After amplifying the signal S2 by the receiving amplifier 6, it is mixed with the transmitted signal S1 by the distributor 7 and the mixer 9. The mixed signal S3 is filtered, and converted into a digital signal by the A/D converter 11 so as to be sampled. This sampled signal S3 is the observation signal outputted by the observation means OB. Although the array radar has a plurality of observation means OB as shown in FIG. 2, the transmitted signals S1 in the respective observation means OB are common.
Next, an example of a pulse radar, which is another instance of observation means OB, will be described. The observation means OB in the pulse radar example is comprised of an oscillator 1, a transmitting amplifier 2, a transmitting antenna 3, a receiving antenna 5, a receiving amplifier 6, a filter 10 and an A/D converter 11, as shown in FIG. 4. The oscillator 1 oscillates pulses which are obtained by dividing a signal having high frequency f0 every equal interval at a cycle of fr[Hz], and the transmitted signal S1 is emitted through the transmitting amplifier 2 and the transmitting antenna 3 (pulse transmission). At the same time, the reflected wave of the transmitted signal S1 is received as a received signal S2 through the receiving antenna 5. After the signal S2 is amplified using the receiving amplifier 6, it is filtered, and is output to the A/D converter 11 through a phase detector (not shown). The signal is converted into digital signal S3 by the A/D converter 11 which is triggered by pulse transmission, and the digital signal S3 is sampled. This sampling signal S3 is the observation signal S3 which the observation means OB outputs. Similar to the FM-CW radar, the transmitted signals S1 used in the respective observation means OB are common.
The means for extracting distance component p (array component p=1, 2, . . . K) as shown in FIG. 2 extracts distance components XRp(r1), . . . XRp(rN) corresponding to distances r1, . . . rN from the observation signals XTp(t1), XTp(t2), XTp(t3), . . . XTp(tM) of one snapshot which are output from the observation means p.
An example of a FM-CW radar will now be described. When a target having velocity V exists at a position of distance r from the receiving antenna 5 (“distance r” being a half of a distance from the transmitting antenna to the receiving antenna via a target. The distance r from the receiving antenna 5 is adopted as “distance r”, provided that the transmitting antenna and the receiving antenna are positioned at the same position. This explanation is applied to all descriptions in the present specification when referring to the distance up to a target r), the observation signals XTp(t1), XTp(t2), XTp(t3), . . . XTp(tM) of the FM-CW radar include a frequency component of fB[Hz] as shown in expression (1).
                    [                  Expression          ⁢                                          ⁢          1                ]                                                                                  f            B                    =                                                                                          4                    ·                    Δ                                    ⁢                                                                          ⁢                  F                                                                      V                    C                                    ·                                      T                    m                                                              ·              r                        ±                                                            2                  ·                                      F                    0                                                                    V                  C                                            ·                              V                ⁡                                  [                  Hz                  ]                                                                    ⁢                                  ⁢                  (                                                    +                                  :                                            ⁢                                                          ⁢              at              ⁢                                                                                ⁢                                                                              ⁢              the              ⁢                                                                                ⁢                                                                              ⁢              time              ⁢                                                                                ⁢                                                                              ⁢              of              ⁢                                                          ⁢              modulation              ⁢                                                                                ⁢                                                                              ⁢              by              ⁢                                                                                ⁢                                                                              ⁢              increasing              ⁢                                                                                ⁢                                                                              ⁢              frequency                        ,                                                  ⁢                                                  ⁢                                          -                                  :                                            ⁢                                                          ⁢              at              ⁢                                                          ⁢              the              ⁢                                                                                ⁢                                                                              ⁢              time              ⁢                                                                                ⁢                                                                              ⁢              of              ⁢                                                          ⁢              modulation              ⁢                                                                                ⁢                                                                              ⁢              by              ⁢                                                          ⁢              decreasing              ⁢                                                                                ⁢                                                                              ⁢              frequency                                )                                    (        1        )            where r denotes distance to a target, V denotes relative velocity of a target, Vc is light speed, ΔF is frequency deviation width of frequency modulation, Tm denotes cycle period of frequency modulation, and Fo denotes central transmitting frequency. If relative velocity is neglected, the following relation which is shown by expression (2) is given between distance r and frequency fB.
                    [                  Expression          ⁢                                                            ⁢                                                          ⁢          2                ]                                                                                  f            B                    =                                                                      4                  ·                  Δ                                ⁢                                                                  ⁢                F                                                              V                  C                                ·                                  T                  m                                                      ·                          r              ⁡                              [                Hz                ]                                                    ⁢                                                      (        2        )            
If respective frequency components fb corresponding to distances r1 through rN are obtained from the observation signals XTp(t1), XTpft2), XTp(t3), . . . XTp(tM) which are time signal series, the components thus obtained are distance components XRp(r1), . . . XRp(rN). If an absolute value of the distance component XRp(rq) is big, it is understood that a target exists at the distance rq. On the contrary, if an absolute value of the distance component XRp(rq) is small, it is understood that a target does not exist at the distance rq. Fourier transformation or filtering with a band-pass filter is used as a method for extracting frequency components.
Besides, a case of a pulse radar is mentioned as another instance. If a target exists at the distance r, an echo from the target is observed in the observation signal at a time
                    [                  Expression          ⁢                                          ⁢          3                ]                                                                      t          e                =                              2                          V              C                                ·          r                                    (        3        )            from a time when emitting a pulse where r denotes distance to the target, and Vc denotes light speed. If the observation signals XTp(t1) XTp(t2), XTp(t3), . . . XTp(tM) are sampled at echo starting times te respectively corresponding to distances r1 through rN, the sampled components are distance components XRp(r1), . . . XRp(rN). Such sampling may be conducted after simple sampling or average filtering.
The means for estimating correlation matrix with exponential smoothing q (distance rq:q=1, 2, . . . N) estimates a correlation matrix Rxxq which represents a correlation characteristics between array components (coherence) from output signals XR1(rq), XR2(rq), . . . XRK(rq) of the means for extracting distance component 1 through K, the output signals being signals relating to the distance rq which is obtained by each array component. The correlation matrix Rxxq is given by Expression (4). In this example, the correlation matrix Rxxq is a complex matrix with K rows and K columns, and a component with i-th row and j-th column is represented by rxxqij.
                    [                  Expression          ⁢                                          ⁢          4                ]                                                                                  R            xxq                    =                                    [                                                                                          r                                              xxq                        ⁢                                                                                                  ⁢                        11                                                                                                  ⋯                                                                              r                                              xx                        ⁢                                                                                                  ⁢                        q                        ⁢                                                                                                  ⁢                        1                        ⁢                        j                                                                                                  ⋯                                                                              r                                              xxq                        ⁢                                                                                                  ⁢                        1                        ⁢                        K                                                                                                                                  ⋮                                                                                                                                                          ⋮                                                                                                                                           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                                      ⁢                          =              Δ                        ⁢                                          [                                                                                                    E                        [                                                  X                          ⁢                                                                                                          ⁢                          R                          ⁢                                                                                                          ⁢                          1                          ⁢                                                      (                            rq                            )                                                    ⁢                          X                          ⁢                                                                                                          ⁢                          R                          ⁢                                                                                                          ⁢                          1                          ⁢                                                                                    (                              rq                              )                                                        *                                                                                                                                      ⋯                                                                                      E                        ⁡                                                  [                                                      XR                            ⁢                                                                                                                  ⁢                            1                            ⁢                                                          (                              rq                              )                                                        ⁢                                                                                          XRj                                ⁡                                                                  (                                  rq                                  )                                                                                            *                                                                                ]                                                                                                            ⋯                                                                                      E                        ⁡                                                  [                                                      XR                            ⁢                                                                                                                  ⁢                            1                            ⁢                                                          (                              rq                              )                                                        ⁢                                                                                          XRK                                ⁡                                                                  (                                  rq                                  )                                                                                            *                                                                                ]                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                          E                        ⁡                                                  [                                                                                    XRi                              ⁡                                                              (                                rq                                )                                                                                      ⁢                            XR                            ⁢                                                                                                                  ⁢                            1                            ⁢                                                                                          (                                rq                                )                                                            *                                                                                ]                                                                                                            ⋯                                                                                      E                        ⁡                                                  [                                                                                    XRi                              ⁡                                                              (                                rq                                )                                                                                      ⁢                                                                                          XRj          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                               XRK                                ⁡                                                                  (                                  rq                                  )                                                                                            *                                                                                ]                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                          E                        ⁡                                                  [                                                                                    XRK                              ⁡                                                              (                                rq                                )                                                                                      ⁢                            XR                            ⁢                                                                                                                  ⁢                            1                            ⁢                                                                                          (                                rq                                )                                                            *                                                                                ]                                                                                                            ⋯                                                                                      E                        ⁡                                                  [                                                                                    XRK                              ⁡                                                              (                                rq                                )                                                                                      ⁢                                                                                          XRj                                ⁡                                                                  (                                  rq                                  )                                                                                            *                                                                                ]                                                                                                            ⋯                                                                                      E                        ⁡                                                  [                                                                                    XRK                              ⁡                                                              (                                rq                                )                                                                                      ⁢                                                                                          XRK                                ⁡                                                                  (                                  rq                                  )                                                                                            *                                                                                ]                                                                                                                    ]                            ⁢                                                          *              represents              ⁢                                                          ⁢              a              ⁢                                                                                ⁢                                                                              ⁢              complex              ⁢                                                                                ⁢                                                                              ⁢                              conjugate                .                                                                  ⁢                                  E                  [                  ]                                            ⁢                                                                                ⁢                                                                              ⁢              represents                                      ⁢                                  ⁢                              an            ⁢                                                                      ⁢                                                                    ⁢            operation            ⁢                                                                      ⁢                                                                    ⁢            for            ⁢                                                  ⁢            obtaining            ⁢                                                                      ⁢                                                                    ⁢            an            ⁢                                                                      ⁢                                                                    ⁢            expected            ⁢                                                                      ⁢                                                                    ⁢            value                    ,                                          ⁢                      and            ⁢                                                                      ⁢                                                                    ⁢            is            ⁢                                                  ⁢            actually            ⁢                                                  ⁢            estimated            ⁢                                                                      ⁢                                                                    ⁢            by            ⁢                                                                      ⁢                                                                    ⁢            time            ⁢                                                                      ⁢                                                                    ⁢            average            ⁢                                                  ⁢            in                          ⁢                                  ⁢                  the          ⁢                                                            ⁢                                                          ⁢          unit          ⁢                                                            ⁢                                                          ⁢          of          ⁢                                                            ⁢                                                          ⁢          one          ⁢                                                            ⁢                                                          ⁢                      snapshot            .                                              (        4        )            
Since the correlation matrix is estimated in snapshots, an estimated value of the correlation matrix after a first snapshot is represented by Rxxq(1), an estimated value after a second snapshot is represented by Rxxq(2), and an estimated value after a m-th snapshot is represented by Rxxq(m). When referring to the distance component in a specific snapshot, the distance rq component of the observation means p in the m-th snapshot is represented by XRp (rq, m), and similar expression is used for the observation signal, also.
With such kind of expression method, a correlation matrix observation value in the m-th snapshot Rtmp_xxq(m) is calculated by an expression (5).
                    [                  Expression          ⁢                                          ⁢          5                ]                                                                      R          tmp_xxq                ⁢                                                       (              m              )                        =                                          [                                                                                                                              r                                                      tmp_xxq                            ⁢                                                                                                                  ⁢                            11                                                                          ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                                                r                                                      tmp_xxq                            ⁢                                                                                                                  ⁢                            1                            ⁢                            j                                                                          ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                                                r                          tmp_xxq1K                                                ⁡                                                  (                          m                          )                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                                                    r                          tmp_xxqi1                                                ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                                                r                          rmp_xxqij                                                ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                                                r                          tmp_xxqiK                                                ⁡                                                  (                          m                          )                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                                                    r                                                      tmp_xxqK                            ⁢                                                                                                                  ⁢                            1                                                                          ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                                                r                          tmp_xxqKj                                                ⁡                                                  (                          m                          )                                                                                                            ⋯                                                                                      r                        tmp_xxqKK                                                                                            ]                            ⁢                                                          ⁢                              =                Δ                            ⁢                              [                                                                                                    XR                        ⁢                                                                                                  ⁢                        1                        ⁢                                                  (                                                      rq                            ,                            m                                                    )                                                ⁢                        XR                        ⁢                                                                                                  ⁢                        1                        ⁢                                                                              (                                                          rq                              ,                              m                                                        )                                                    *                                                                                                            ⋯                                                                                      XR                        ⁢                                                                   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          ⁢                                                                                                  ⁢                        1                        ⁢                                                  (                                                      rq                            ,                            m                                                    )                                                ⁢                                                                              XRK                            ⁡                                                          (                                                              rq                                ,                                m                                                            )                                                                                *                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                                                    XRi                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                        XR                        ⁢                                                                                                  ⁢                        1                        ⁢                                                                              (                                                          rq                              ,                              m                                                        )                                                    *                                                                                                            ⋯                                                                                                                XRi                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                                                                              XRj                            ⁡                                                          (                                                              rq                                ,                                m                                                            )                                                                                *                                                                                                            ⋯                                                                                                                XRi                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                                                                              XRK                            ⁡                                                          (                                                              rq                                ,                                m                                                            )                                                                                *                                                                                                                                                ⋮                                                                                                                                                                          ⋮                                                                                                                                                                          ⋮                                                                                                                                                    XRK                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                        XR                        ⁢                                                                                                  ⁢                        1                        ⁢                                                                              (                                                          rq                              ,                              m                                                        )                                                    *                                                                                                            ⋯                                                                                                                XRK                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                                                                              XRj                            ⁡                                                          (                                                              rq                                ,                                m                                                            )                                                                                *                                                                                                            ⋯                                                                                                                XRK                          ⁡                                                      (                                                          rq                              ,                              m                                                        )                                                                          ⁢                                                                              XRK                            ⁡                                                          (                                                              rq                                ,                                m                                                            )                                                                                *                                                                                                                    ]                                                                        (        5        )            
As a method of estimating a correlation matrix, a section average type and an exponential smoothing type are well-known.
In the method of estimating correlation matrix with section average, an average value between correlation matrix observation values of snapshots which continues predetermined SSN [times] is used as an estimated value of the correlation matrix. A number of sampling SSN [times] for equalization relates to S/N improvement. If SSN becomes bigger, the influence of noise in an observation signal is removed, so that S/N improves. One of the methods of calculating the estimated value is shown in an expression (6)
                    [                  Expression          ⁢                                          ⁢          6                ]                                                                                  R            xxq                    ⁡                      (            m            )                          =                              1            SSN                    ⁢                                    ∑                              j                =                0                                            SSN                -                1                                      ⁢                                          R                tmp_xxq                            ⁡                              (                                  m                  -                  j                                )                                                                        (        6        )            
Although this refers to a case where the estimated value of the correlation matrix is renewed, synchronizing with the snapshot, the renewal cycle of the estimated value of the correlation matrix may be once SSN snapshot times. In such a case, the estimated value of the correlation matrix is renewed as shown by an expression (7)
                              [                      Expression            ⁢                                                  ⁢            7                    ]                ⁢                                  ⁢                                            R              xxq                        ⁡                          (                              m                ′                            )                                =                                    1              SSN                        ⁢                                          ∑                                  j                  =                  1                                SSN                            ⁢                                                R                  imp_xxq                                ⁡                                  (                                                            SSN                      ·                                              (                                                                              m                            ′                                                    -                          1                                                )                                                              +                    j                                    )                                                                                        (        7        )            where Rxxq(m′) means the estimated value of the correlation matrix which is renewed in the m′-th snapshot.
The method of estimating correlation matrix with exponential smoothing is one of obtaining the estimated value of the correlation matrix by respectively weighting the estimated value of the correlation matrix of the last snapshot and the observation value of the correlation matrix which is obtained in the present snapshot and adding them together. A weight of the estimated value of the correlation matrix of the last snapshot is referred to as a forgetting factor, and is represented by α. At this time, a weight of the observation value of the correlation matrix which is obtained in the present snapshot is 1-α. A method of calculating the estimated value in the method of estimating correlation matrix with exponential smoothing is shown in expression (8).
[Expression 8]Rxxq(m)=α·Rxxq(m−1)+(1−α)·Rtmp—xxq(m)  (8)
The number of sampling SSN [times] for equalization in the section average method which has been mentioned before and the forgetting factor α have the following relation as shown by expression (9) in view of dispersion of the estimated value.
                    [                  Expression          ⁢                                                            ⁢                                                          ⁢          9                ]                                                            α        =                              SSN            -            1                                SSN            +            1                                              (        9        )            
Expression (9) is introduced by such a condition where dispersion of the estimated value is equal in the section average method and the exponential smoothing method if each element of the observation value of the correlation matrix conforms to a chi-square distribution of degree of freedom 2, but this will not be described in detail. Then, SSN is made bigger as a approximates 1, so that the effect of the S/N improvement is made bigger. Therefore, the forgetting factor α is a parameter for adjusting the S/N improvement.
If expression (8) is accepted as an IIR filter, a transient response performance on a change of the observation value of the correlation matrix is improved when a approximates zero (0), so that the forgetting factor α is a parameter for adjusting the transient response performance.
In the array radar apparatus as shown in FIG. 2, the means for estimating correlation matrix with exponential smoothing q (distance component rq: q=1, 2, . . . N) executes the estimating method of expression (8), and the correlation matrix estimated value Rxxq corresponding to each distance component rq is output to the means for estimating presence and movement state of target OM.
The means for estimating presence and movement state of target OM estimates the presence of a target and a movement state of the target from the correlation matrix estimated values Rxx1 through RxxN corresponding to the distances r1 through rN. FIG. 5 shows an example of its schematic structure.
The means for estimating presence and movement state of a target OM of FIG. 5 is comprised of means for computing angular spectrum corresponding to the distances r1 through rN, which are denoted with reference numerals AS, and data association means which is denoted with a reference numeral DA.
The means for computing angular spectrum q (distance rq:q=1, 2, . . . N) computes an angular spectrum Pq(θ) from the estimated value of the correlation matrix. The angular spectrum represents a power angular distribution, and Pq(θ1) represents a power which arrives from the azimuth θ1. Known computing method include a beamformer method, a Capon's method, a Linear Prediction method, MUSIC, ESPRIT and the like (see non-patent-related document 1). In the MUSIC or ESPRIT methods, power can not be directly obtained, so it may be referred to as a pseudo spectrum. All angular spectra including pseudo spectra are referred to as only angular spectra in the present embodiment. An intense reflected wave is considered to arrive from an angle where the spectral intensity is intense in the angular spectra, so that a target is predicted to be in this azimuth. In the case of the angular spectrum Pq(θ) as shown in FIG. 6, for instance, a target is predicted to be at θ1, θ2 and θ3 [°], which spectrum intensities are intense.
The data association means DA estimates the presence and a movement state of a target by inputting the angular spectra P1(θ) through PN(θ) corresponding to the distances r1 through rN. If the angular spectrum of FIG. 6 is inputted as one of the distance rq, for instance, the data association means DA estimates the presence of three targets (distance, azimuth)=(rq, θ1), (distance, azimuth)=(rq, θ2) and (distance, azimuth)=(rq, θ3). If the angular spectrum of FIG. 7 is inputted as one of the distance rq, for instance, the data association means DA estimates no presence of target at the distance rq. The above-mentioned example is a very simplified estimation example. The positioning estimation accuracy may be increased by estimation with a combination of the angular spectra P1(θ) through PN(θ) in a plurality of snapshots. In addition, the movement state, such as the velocity or the acceleration of the target, may be estimated in such a manner that a tracking process in an axial direction of the snapshot is applied to positioning information which is obtained from the angular spectrum.
In case of the FM-CW radar, the velocity of the target may be detected by Doppler effect by comparing two kinds of the angular spectra 1 through N, the snapshot at the time of modulation by increasing frequency, and the snapshot at the time of modulation by decreasing frequency.
Further, the movement state of the target may be known in such a way that the angular spectra 1 through N are overlapped with each other so as to prepare a two-dimensional distance-angular spectrum, and the prepared spectrum is treated as an image and is recognized by patterns (see non-patent-related document 2).
[Non-patent-related document 1] “Adaptive antenna technique” has been published on Oct. 10, 2003 by Ohmsha written by Nobuo KIKUMA
[Non-patent-related document 2] “Radar signal processing technique” has been published on Sep. 20, 1991 by “The institute of Electronics, Information and Communication Engineers” written by Matsuo SEKINE, the chapter 10 “Pattern recognition in radar signal processing”.
The above-mentioned examples describe the structure of the array radar signal processor for estimating the presence and the movement state of the target. In order to accurately estimate the presence and the movement state of the target, it is necessary to properly estimate the correlation matrix which is the intermediate data.
It is difficult to properly estimate the correlation matrix in the vehicle-mounted radar due a number of factors, including: distance attenuation of the reflected wave from the target, a change of a reflected wave from a target which arises from a change of the movement state of ones own vehicle, such as the change in turning and the change of speed, a change of a reflected wave from a target which arises from a change of the surroundings of ones own vehicle, such as the change in the speed of the peripheral vehicle, and a change of a radio wave state, such as an influence of an interfering wave.
The object of the invention is to provide a radar signal processor for properly estimating the correlation matrix according to the distance attenuation of the reflected wave from the target, the change of the reflected wave due to the changes of the movement state and surroundings of ones own vehicle, and the radio wave state.